Technique for calibrating a positioning system

ABSTRACT

Calibrating a positioning system comprising a plurality of anchor nodes used to determine tag positions within a localization area using radio technology. The method includes performing, at a plurality of first measurement points in the localization area using the localization tag, first ranging measurements with respect to the plurality of anchor nodes using the radio technology to determine respective first distances from the measurement device to the plurality of anchor nodes and performing, at the plurality of first measurement points using the at least one odometry sensor, first odometry measurements to estimate respective first positions of the measurement device in the localization area, estimating locations of the plurality of anchor nodes based on the respective first distances determined by the first ranging measurements and the respective first positions estimated by the first odometry measurements, and calibrating the positioning system using the estimated locations of the plurality of anchor nodes.

TECHNICAL FIELD

The present disclosure generally relates to the field of positioningsystems. In particular, a technique for calibrating a positioning systemcomprising a plurality of anchor nodes used to determine tag positionswithin a localization area using radio technology is presented. Thetechnique may be embodied in methods, computer programs, apparatuses andsystems.

BACKGROUND

In environments where positioning technologies such as the GlobalPositioning System (GPS) are unavailable or not accurate enough (e.g.,in indoor environments), high precision positioning systems may beinstalled to allow object location detection with even a centimeterlevel of accuracy. High precision positioning systems may be based onUltra Wideband (UWB) technology, for example, and typically comprise afixedly deployed set of anchor nodes (e.g., installed on ceiling orwalls) and a variable set of movable tag devices (e.g., attached toobjects, such as to workpieces in a factory) and whose locations need tobe determined.

An exemplary architecture of such system is illustrated in FIG. 1, wheretag devices can communicate with anchor nodes using radio technology,e.g., using short signal pulses, to perform two-way timing measurementsof the time the signals travel between a tag device and an anchor nodeto thereby measure the distance therebetween. This process is called“ranging”. The position of the tag devices can be determined based onsuch ranging measurements, taking into consideration the known fixedcoordinates of the anchor nodes. As shown in the figure, the rangingmeasurements performed between the anchor nodes and the tag devices maybe delivered to a cloud (e.g., to a cloud based positioning service),where the positions of the tag devices can be calculated based on theranging measurements. The cloud may then provide various services toupper layer applications available via respective ApplicationProgramming Interfaces (APIs) and provide the calculated positions ofthe tag devices for further processing, or send alerts when a tag deviceapproaches a restricted area, for example.

Before the positioning system can be put into operation, the anchornodes need to be deployed first and their exact position in thethree-dimensional space needs to be configured in the system forcalibration purposes. In the simplest case, the position of the anchornodes may be measured manually with laser distance measuring devices andmay be preconfigured in the system. However, such approach is generallycumbersome and may not always be feasible, e.g., when anchor nodes areinstalled at locations that are difficult to reach or not reachable atall (e.g., at certain portions of ceilings or walls). Other solutionstry to simplify this process by collecting a large set of rangingmeasurements data and then calculating the most probable anchorpositions that explain the collected data in the best possible way.

One such solution is disclosed in U.S. Pat. No. 8,344,948 B2 andinvolves collecting a first set of data by placing a tag device close toeach anchor node and obtain a first rough estimate of the anchor nodecoordinates. In a second step, data may be collected by walking with thetag device in the measurement space and an optimization algorithm may beexecuted to estimate the most probable tag trajectory as well as theanchor node positions. The method assumes a model of the signal time ofarrival measurements with Gaussian errors and the optimization isfocused on estimating the model parameters. However, this method assumes“clean” measurements, i.e., line of sight only measurements, whichrequires some filtering beforehand and, further, the assumed model dealswith Gaussian errors only which can be quite limiting and inaccurate inpractice.

Another solution is disclosed in US 2015/0094081 A1 which is based onperforming ranging measurements between access points and determiningtheir relative coordinates based on these measurements. The process maybe started off with three neighboring anchor nodes which mutuallymeasure each other and, then, additional neighboring anchors may beadded one-by-one, determining their positions based on the alreadyselected anchors. In this method, measurements between anchor nodes mayentail constant errors, e.g., originating from non-line of sightmeasurements, and the resulting anchor node coordinates may therefore beinaccurate as well.

As can be seen from these examples, current solutions for configuringthe positions of anchor nodes for calibration purposes may either makeinfeasible assumptions that lead to inaccurate results (e.g., due tonon-realistic assumptions, such as Gaussian errors, the availability ofclean line of sight measurements only, or error-free anchor-to-anchorranging) or may require infeasible measurement collections, such as theneed to move tag devices close to the anchor nodes, which may beimpossible when the anchor nodes are deployed at hardly reachablelocations.

SUMMARY

Accordingly, there is a need for a technique which avoids one or more ofthe problems discussed above, or other problems.

According to a first aspect, a method for calibrating a positioningsystem comprising a plurality of anchor nodes used to determine tagpositions within a localization area using radio technology is provided.The method is performed using a measurement device comprising at leastone odometry sensor and a localization tag configured to communicatewith the plurality of anchor nodes using the radio technology. Themethod comprises performing, at a plurality of first measurement pointsin the localization area using the localization tag, first rangingmeasurements with respect to the plurality of anchor nodes using theradio technology to determine respective first distances from themeasurement device to the plurality of anchor nodes and performing, atthe plurality of first measurement points using the at least oneodometry sensor, first odometry measurements to estimate respectivefirst positions of the measurement device in the localization area,estimating locations of the plurality of anchor nodes based on therespective first distances determined by the first ranging measurementsand the respective first positions estimated by the first odometrymeasurements, and configuring the positioning system with the estimatedlocations of the plurality of anchor nodes to calibrate the positioningsystem.

The first ranging measurements and the first odometry measurements maybe performed periodically when moving the measurement device through thelocalization area. The respective first distances determined by thefirst ranging measurements and the respective first positions estimatedby the first odometry measurements may be stored in a first measurementdataset, wherein, in the first measurement dataset, each positionestimated by an odometry measurement may be stored in association withcorresponding distances to visible anchor nodes determined by rangingmeasurements at the same measurement point. The respective firstdistances determined by the first ranging measurements and therespective first positions estimated by the first odometry measurementsmay be transferred from the measurement device to a server, whereinestimating the locations of the plurality of anchor nodes may beperformed by the server. Transferring the respective first distancesdetermined by the first ranging measurements and the respective firstpositions estimated by the first odometry measurements from themeasurement device to the server may be performed batchwise whileperforming the first ranging measurements and the first odometrymeasurements.

Estimating the locations of the plurality of anchor nodes may includecompensating drifts in the respective first positions estimated by thefirst odometry measurements. Compensating the drifts in the respectivefirst positions estimated by the first odometry measurements may includeat least one of rotating and scaling the respective first positions withrespect to at least one known landmark position. Estimating thelocations of the plurality of anchor nodes may include executing atleast two location estimation algorithms having differentcharacteristics with regard to error robustness, and combining theresults of the at least two location estimation algorithms. The at leasttwo location estimation algorithms may comprise a crosspoint basedalgorithm which includes calculating crosspoints of spheres as candidatelocations of anchor nodes, the spheres having centers corresponding tothe first positions estimated by the first odometry measurements andhaving radii corresponding to the associated first distances determinedby the first ranging measurements. A location of an anchor node may beestimated by determining a cluster head that is closest to thecalculated crosspoints. The crosspoint based algorithm may furtherinclude filtering out crosspoints for which there are rangingmeasurements with a distance smaller than a distance between therespective crosspoint and a corresponding first position estimated bythe first odometry measurements by a predetermined threshold. The atleast two location estimation algorithms may also comprise anoptimization algorithm which includes solving an optimization problem tooptimally fit the locations of the plurality of anchor nodes with thefirst ranging measurements and the first odometry measurements. In theoptimization algorithm, the respective first positions estimated by thefirst odometry measurements may be treated as known positions in theoptimization problem.

The method may further comprise performing, at a plurality of secondmeasurement points in the localization area using the localization tag,second ranging measurements with respect to the plurality of anchornodes using the radio technology to determine respective seconddistances from the measurement device to the plurality of anchor nodesand performing, at the plurality of second measurement points using theat least one odometry sensor, second odometry measurements to estimaterespective second positions of the measurement device in thelocalization area, and validating the estimated locations of theplurality of anchor nodes based on the second distances determined bythe second ranging measurements and the second positions estimated bythe second odometry measurements. Validating the estimated locations ofthe plurality of anchor nodes may be performed considering at least oneof a number of undershoot measurements corresponding to a number oftimes one of the second distances is smaller than a distance between theassociated second position and the estimated location of thecorresponding anchor node being validated, a number of line of sightmeasurements corresponding to a number of times one of the seconddistances coincides with a distance between the associated secondposition and the estimated location of the corresponding anchor nodebeing validated, and an angular distribution of the line of sightmeasurements in space.

When one or more of the estimated locations of the plurality of anchornodes are validated negatively, the method may further compriseperforming, at a plurality of third measurement points in thelocalization area using the localization tag, third ranging measurementswith respect to the one or more negatively validated anchor nodes usingthe radio technology to determine respective third distances from themeasurement device to the one or more negatively validated anchor nodesand performing, at the plurality of third measurement points using theat least one odometry sensor, third odometry measurements to estimaterespective third positions of the measurement device in the localizationarea, and refining the estimated locations of the one or more negativelyvalidated anchor nodes based on the respective third distancesdetermined by the third ranging measurements and the respective thirdpositions estimated by the third odometry measurements. The method mayfurther comprise providing guidance for re-measuring the one or morenegatively validated anchor nodes. Also, the method may further compriseproviding feedback on whether the third ranging measurements correspondto line of sight measurements.

According to a second aspect, a measurement device for supportingcalibration of a positioning system comprising a plurality of anchornodes used to determine tag positions within a localization area usingradio technology is provided. The measurement device comprises at leastone odometry sensor and a localization tag configured to communicatewith the plurality of anchor nodes using the radio technology. Themeasurement device is configured to perform the steps of performing, ata plurality of first measurement points in the localization area usingthe localization tag, first ranging measurements with respect to theplurality of anchor nodes using the radio technology to determinerespective first distances from the measurement device to the pluralityof anchor nodes and performing, at the plurality of first measurementpoints using the at least one odometry sensor, first odometrymeasurements to estimate respective first positions of the measurementdevice in the localization area, and providing the respective firstdistances determined by the first ranging measurements and therespective first positions estimated by the first odometry measurementsto a configuration component for calibration of the positioning system.

As in the method of the first aspect, the first ranging measurements andthe first odometry measurements may be performed periodically when themeasurement device is moved through the localization area. Therespective first distances determined by the first ranging measurementsand the respective first positions estimated by the first odometrymeasurements may be stored in a first measurement dataset, wherein, inthe first measurement dataset, each position estimated by an odometrymeasurement may be stored in association with corresponding distances tovisible anchor nodes determined by ranging measurements at the samemeasurement point. The configuration component may be executed on aserver, wherein the respective first distances determined by the firstranging measurements and the respective first positions estimated by thefirst odometry measurements may be transferred from the measurementdevice to the configuration component. Transferring the respective firstdistances determined by the first ranging measurements and therespective first positions estimated by the first odometry measurementsfrom the measurement device to the server may be performed batchwisewhile performing the first ranging measurements and the first odometrymeasurements.

The measurement device may further be configured to perform the steps ofperforming, at a plurality of second measurement points in thelocalization area using the localization tag, second rangingmeasurements with respect to the plurality of anchor nodes using theradio technology to determine respective second distances from themeasurement device to the plurality of anchor nodes and performing, atthe plurality of second measurement points using the at least oneodometry sensor, second odometry measurements to estimate respectivesecond positions of the measurement device in the localization area, andproviding the respective second distances determined by the secondranging measurements and the respective second positions estimated bythe second odometry measurements to the configuration component forcalibration of the positioning system. Also, the measurement device mayfurther be configured to perform the steps of performing, at a pluralityof third measurement points in the localization area using thelocalization tag, third ranging measurements with respect to one or morenegatively validated anchor nodes using the radio technology todetermine respective third distances from the measurement device to theone or more negatively validated anchor nodes and performing, at theplurality of third measurement points using the at least one odometrysensor, third odometry measurements to estimate respective thirdpositions of the measurement device in the localization area, andproviding the respective third distances determined by the third rangingmeasurements and the respective third positions estimated by the thirdodometry measurements to the configuration component for calibration ofthe positioning system. The measurement device may further be configuredto perform the step of providing guidance for re-measuring the one ormore negatively validated anchor nodes. Also, the measurement device mayfurther be configured to perform the step of providing feedback onwhether third ranging measurements correspond to line of sightmeasurements.

According to a third aspect, a configuration component for supportingcalibration of a positioning system comprising a plurality of anchornodes used to determine tag positions within a localization area usingradio technology is provided. The configuration component is configuredto perform the steps of obtaining, from a measurement device, respectivefirst distances from the measurement device to the plurality of anchornodes determined by first ranging measurements performed by themeasurement device at a plurality of first measurement points in thelocalization area using a localization tag of the measurement device,and respective first positions of the measurement device in thelocalization area estimated by first odometry measurements performed bythe measurement device at the plurality of first measurement pointsusing at least one odometry sensor of the measurement device, estimatinglocations of the plurality of anchor nodes based on the respective firstdistances determined by the first ranging measurements and therespective first positions estimated by the first odometry measurements,and configuring the positioning system with the estimated locations ofthe plurality of anchor nodes to calibrate the positioning system.

As in the method of the first aspect, estimating the locations of theplurality of anchor nodes may include compensating drifts in therespective first positions estimated by the first odometry measurements.Compensating the drifts in the respective first positions estimated bythe first odometry measurements may include at least one of rotating andscaling the respective first positions with respect to at least oneknown landmark position. Estimating the locations of the plurality ofanchor nodes may include executing at least two location estimationalgorithms having different characteristics with regard to errorrobustness, and combining the results of the at least two locationestimation algorithms. The at least two location estimation algorithmsmay comprise a crosspoint based algorithm which includes calculatingcrosspoints of spheres as candidate locations of anchor nodes, thespheres having centers corresponding to the first positions estimated bythe first odometry measurements and having radii corresponding to theassociated first distances determined by the first ranging measurements.A location of an anchor node may be estimated by determining a clusterhead that is closest to the calculated crosspoints. The crosspoint basedalgorithm may further include filtering out crosspoints for which thereare ranging measurements with a distance smaller than a distance betweenthe respective crosspoint and a corresponding first position estimatedby the first odometry measurements by a predetermined threshold. The atleast two location estimation algorithms may also comprise anoptimization algorithm which includes solving an optimization problem tooptimally fit the locations of the plurality of anchor nodes with thefirst ranging measurements and the first odometry measurements. In theoptimization algorithm, the respective first positions estimated by thefirst odometry measurements may be treated as known positions in theoptimization problem.

The configuration component may further be configured to perform thesteps of obtaining, from the measurement device, respective seconddistances from the measurement device to the plurality of anchor nodesdetermined by second ranging measurements performed by the measurementdevice at a plurality of second measurement points in the localizationarea using the localization tag of the measurement device with respectto the plurality of anchor nodes, and respective second positions of themeasurement device in the localization area estimated by second odometrymeasurements performed by the measurement device at the plurality ofsecond measurement points using at least one odometry sensor of themeasurement device, and validating the estimated locations of theplurality of anchor nodes based on the second distances determined bythe second ranging measurements and the second positions estimated bythe second odometry measurements. Validating the estimated locations ofthe plurality of anchor nodes may be performed considering at least oneof a number of undershoot measurements corresponding to a number oftimes one of the second distances is smaller than a distance between theassociated second position and the estimated location of thecorresponding anchor node being validated, a number of line of sightmeasurements corresponding to a number of times one of the seconddistances coincides with a distance between the associated secondposition and the estimated location of the corresponding anchor nodebeing validated, and an angular distribution of the line of sightmeasurements in space.

When one or more of the estimated locations of the plurality of anchornodes are validated negatively, the configuration component may furtherbe configured to perform the steps of obtaining, from the measurementdevice, respective third distances from the measurement device to theplurality of anchor nodes determined by third ranging measurementsperformed by the measurement device at a plurality of third measurementpoints in the localization area using the localization tag of themeasurement device with respect to the one or more negatively validatedanchor nodes, and respective third positions of the measurement devicein the localization area estimated by third odometry measurementsperformed by the measurement device at the plurality of thirdmeasurement points using at least one odometry sensor of the measurementdevice, and refining the estimated locations of the one or morenegatively validated anchor nodes based on the respective thirddistances determined by the third ranging measurements and therespective third positions estimated by the third odometry measurements.

According to a fourth aspect, a computer program product is provided.The computer program product comprises program code portions forperforming the steps specified in at least one of the second aspect andthe third aspect when the computer program product is executed on one ormore computing devices (e.g., a processor or a distributed set ofprocessors). The computer program product may be stored on a computerreadable recording medium, such as a semiconductor memory, DVD, CD-ROM,and so on.

According to a fifth aspect, there is provided a system comprising ameasurement device according to the second aspect and a configurationcomponent according to the third aspect.

BRIEF DESCRIPTION OF THE DRAWINGS

Implementations of the technique presented herein are described hereinbelow with reference to the accompanying drawings, in which:

FIG. 1 illustrates an exemplary architecture of a positioning systemcomprising anchor nodes and tag devices in a localization area, whereina cloud based positioning service determines the positions of the tagdevices based on ranging measurements performed between the anchor nodesand the tag devices;

FIG. 2 illustrates a method for calibrating a positioning systemaccording to the present disclosure;

FIG. 3 illustrates an exemplary measurement device according to thepresent disclosure;

FIG. 4 illustrates an exemplary measurement path along which ameasurement device may be moved in a localization area;

FIGS. 5a and 5b illustrate exemplary crosspoints of spheres and acorresponding cluster head calculated as part of a crosspoint basedalgorithm according to the present disclosure;

FIGS. 6a and 6b illustrate exemplary compositions of a measurementdevice and a configuration component according to the presentdisclosure;

FIG. 7 illustrates a flowchart of an exemplary calibration procedureaccording to the present disclosure;

FIG. 8 illustrates a result of the calibration procedure for an actualdeployment according to the present disclosure; and

FIG. 9 illustrates exemplary validation statistics obtained for anactual deployment according to the present disclosure.

DETAILED DESCRIPTION

In the following description, for purposes of explanation and notlimitation, specific details are set forth in order to provide athorough understanding of the present disclosure. It will be apparent toone skilled in the art that the present disclosure may be practiced inother embodiments that depart from these specific details.

Those skilled in the art will further appreciate that the steps,services and functions explained herein below may be implemented usingindividual hardware circuitry, using software functioning in conjunctionwith a programmed micro-processor or general purpose computer, using oneor more Application Specific Integrated Circuits (ASICs) and/or usingone or more Digital Signal Processors (DSPs). It will also beappreciated that when the present disclosure is described in terms of amethod, it may also be embodied in one or more processors and one ormore memories coupled to the one or more processors, wherein the one ormore memories are encoded with one or more programs that perform thesteps, services and functions disclosed herein when executed by the oneor more processors.

FIG. 2 illustrates a method for calibrating a positioning systemaccording to the present disclosure. The positioning system comprises aplurality of anchor nodes used to determine tag positions within alocalization area using radio technology. The method is performed usinga measurement device comprising at least one odometry sensor and alocalization tag configured to communicate with the plurality of anchornodes using the radio technology. The method comprises performing, instep S202, at a plurality of first measurement points in thelocalization area using the localization tag, first ranging measurementswith respect to the plurality of anchor nodes using the radio technologyto determine respective first distances from the measurement device tothe plurality of anchor nodes and performing, at the plurality of firstmeasurement points using the at least one odometry sensor, firstodometry measurements to estimate respective first positions of themeasurement device in the localization area. The method furthercomprises estimating, in step S204, locations of the plurality of anchornodes based on the respective first distances determined by the firstranging measurements and the respective first positions estimated by thefirst odometry measurements and, in step S206, configuring thepositioning system with the estimated locations of the plurality ofanchor nodes to calibrate the positioning system.

To perform calibration measurements, a measurement device may thus beemployed which includes both at least one odometry sensor and alocalization tag that is configured to communicate with the plurality ofanchor nodes using the radio technology. The localization tag maycorrespond to a tag device described above for systems of the prior art.The radio technology may be UWB technology, for example. The measurementdevice may be provided in the form of a portable device, such as a smartphone or tablet, for example, that may be carried through thelocalization area to perform the calibration procedure. As known to theperson skilled in the art, odometry generally relates to the use of datafrom motion sensors to estimate a change in position over time (e.g.,relative to a start position). The at least one odometry sensor may thuscomprise at least one sensor capable to measure a movement of themeasurement device in the three-dimensional space and may include acamera, an inertial sensor or a depth sensor, for example. Odometrymeasurements may relate to relative movements of the measurement devicedetermined by the at least one odometry sensor. The localization tag maybe mounted on the measurement device in such a way that the localizationtag is as close as possible to (e.g., adjacent to) the at least oneodometry sensor and that its relative position to the at least oneodometry sensor is fixed. An exemplary measurement device is illustratedin FIG. 3, where the device is provided in the form of a smart phone 300with a localization tag 302 mounted next to the camera 304 of the smartphone 300 and where the localization tag 302 is connected to the smartphone via a USB connection.

The localization area may correspond to the area that is coverable bythe radio range of the plurality of anchor nodes, i.e., the area inwhich the plurality of anchor nodes may perform ranging measurementswith localization tags using the radio technology. Each of the pluralityof anchor nodes may be configured to communicate with localization tagsin the localization area using the radio technology and, morespecifically, perform ranging measurements with respect to localizationtags in the localization area using the radio technology. Thepositioning system may be configured to locate the localization tags inthe localization area based on the ranging measurements performedbetween the plurality of anchor nodes and the localization tags.

For calibration purposes, the measurement device may be moved throughthe localization area along a measurement path (e.g., a random walk)which includes the plurality of first measurement points, wherein, ateach of the plurality of first measurement points, a ranging measurementmay be performed with respect to the plurality of anchor nodes using theradio technology to determine a corresponding distance from themeasurement device (more specifically, from the localization tag of themeasurement device) to each (visible) anchor node among the plurality ofanchor nodes at that measurement point, resulting in the “respectivefirst distances” determined by the “first ranging measurements” in stepS202 mentioned above. In order to obtain more accurate measurement datafor the calibration of the positioning system, odometry measurements maybe performed—in addition to the ranging measurements—at the samemeasurement points in the measurement path.

That is, at each of the plurality of first measurement points, anodometry measurement may be performed in addition to the rangingmeasurement to estimate a corresponding position of the measurementdevice in the localization area at that measurement point, resulting inthe “respective first positions” determined by the “first odometrymeasurements” in step S202 mentioned above. An exemplary measurementpath through the localization area made up by a plurality of anchornodes 400 is illustrated in FIG. 4, where the small circles representthe estimated positions (with some uncertainty) of the measurementdevice being carried along the random walk.

Before the measurement procedure is started, at least onesynchronization landmark whose exact position is known may bedesignated. This may be a corner point or the position of a specialobject, for example. The coordinates of such landmarks in thethree-dimensional space may be manually preconfigured or read out of amap, for example. As the measurement device is carried through thelocalization area and reaches a synchronization landmark, themeasurement device may be placed as close as possible to the landmark torecord the position of the landmark (e.g., by pushing a “landmarkbutton” on the smart phone 300 to indicate that a known position hasbeen reached). Such recording of landmarks may later be helpful incompensating drifts in the odometry measurements, as will be describedin more detail below.

As the measurement device is carried through the localization area, thefirst ranging measurements and the first odometry measurements may beperformed continuously (e.g., periodically), wherein the results of thefirst ranging measurements and the first odometry measurements may berecorded on the measurement device (e.g., logged into a log file). Thefirst ranging measurements and the first odometry measurements may thusbe performed periodically when moving the measurement device through thelocalization area and, further, the respective first distancesdetermined by the first ranging measurements and the respective firstpositions estimated by the first odometry measurements may be stored ina first measurement dataset, wherein, in the first measurement dataset,each position estimated by an odometry measurement may be stored inassociation with corresponding distances to visible anchor nodes (amongthe plurality of anchor nodes) determined by ranging measurements at thesame measurement point. In other words, the first odometry measurementsmay be combined with the first ranging measurements obtained from thelocalization tag, such that each odometry measurement is combined withthe next (or previous) ranging measurement (e.g., which is closest intime) in the measurement dataset. In still in other words, eachmeasurement point may have an associated range measurement vector thatincludes all anchor nodes visible and measured at that measurementpoint. The measurement dataset may be populated as the measurementdevice is moved through the localization area, e.g., by logging therespective measurements into the log file and storing the fileaccordingly. All this behavior of the measurement device may realized bya measurement collection software executed on the measurement device,e.g., in accordance with a preset configuration.

Based on the determined first distances and the estimated firstpositions, the locations of the plurality of anchor nodes may beestimated in step S204 and the positioning system may be configured withthe estimated locations of the plurality of anchor nodes to calibratethe positioning system in the step S206, as described above. While it isgenerally conceivable that these steps are performed by the measurementdevice itself, it may also be conceivable that at least one of thesesteps is performed remotely from the measurement device. To this end,the respective first distances determined by the first rangingmeasurements and the respective first positions estimated by the firstodometry measurements may be transferred (or “provided”) from themeasurement device to a server, wherein estimating the locations of theplurality of anchor nodes may then be performed by the server. Theserver may reside in a cloud, for example. A configuration componentexecuted on the server may receive (or “obtain”) the respective firstdistances and the respective first positions from the measurement deviceand may process them in line with steps S204 and S206.

While the measurement dataset recorded by the measurement device may betransferred to the server after the generation of the measurementdataset is complete (e.g., upload the complete log file to the serverwhen the random walk in the localization area with the measurementdevice is finished), the transfer may also be performed in smallerbatches while the measurement procedure is still ongoing. In otherwords, transferring the respective first distances determined by thefirst ranging measurements and the respective first positions estimatedby the first odometry measurements from the measurement device to theserver may be performed batchwise while performing the first rangingmeasurements and the first odometry measurements. In this way, a user ofthe measurement device may get continuous feedback from the server aboutcurrent best anchor position estimates as well as hints as to whichestimated anchor node location still requires a more precisemeasurement, so that the measurement device can be carried to those“white spots” in a targeted way. This will be described in more detailbelow with reference to the validation procedure.

For the purpose of estimating the locations of the plurality of anchornodes in accordance with step S204, possible drifts in the odometrymeasurements may be compensated by matching measurement samples around asynchronization landmark to the exact known position of the landmark.Estimating the locations of the plurality of anchor nodes may thusinclude compensating drifts in the respective first positions estimatedby the first odometry measurements. This may include a rotation and/orscaling of all odometry measurement points on the measurement path suchthat the measurement points around the landmarks exactly fit the knownpositions of the landmarks. Compensating the drifts in the respectivefirst positions estimated by the first odometry measurements may thusinclude at least one of rotating and scaling the respective firstpositions with respect to at least one known landmark position.

The first ranging measurements and the (optionally, drift compensated)first positions may then be input to an anchor node location estimationalgorithm. While it will be understood that various algorithms can beused to calculate the anchor node positions, in one particularimplementation, estimating the locations of the plurality of anchornodes may include executing at least two location estimation algorithmshaving different characteristics with regard to error robustness, andcombining the results of the at least two location estimationalgorithms. In particular, one of these estimation algorithms may berobust against one type of errors while, while another estimationalgorithm may be robust against another type of errors, to therebyminimize the error of the combined procedure. Also, other than the priorart systems described above, the estimation algorithms may take noa-priori assumptions about error models or line of sight/non-line ofsight measurements, for example.

In one variant, the at least two location estimation algorithms maycomprise a crosspoint based algorithm which includes calculatingcrosspoints of spheres as candidate locations of anchor nodes, thespheres having centers corresponding to the first positions estimated bythe first odometry measurements and having radii corresponding to theassociated first distances determined by the first ranging measurements.In other words, the crosspoint based algorithm may include calculatingcrosspoints of spheres taken around the measurement points with theranging measurements representing the radii, wherein crosspoints ofspheres are taken as potential anchor node positions. An exemplaryillustration of such a scenario is illustrated in FIG. 5a . A locationof an anchor node may then be estimated by determining a cluster headthat is closest to the calculated crosspoints. Such situation is shownin FIG. 5b , where the cluster head 500 is determined to be closest toall calculated crosspoints for a particular anchor node so that thecluster head 500 is assumed as the exact location of that anchor node.

As there may be a large number of spheres and crosspoints, a filteringoperation may be applied such that crosspoints that are in conflict withany ranging measurement are removed. The crosspoint based algorithm maythus further include filtering out crosspoints for which there areranging measurements with a distance smaller than a distance between therespective crosspoint and a corresponding first position estimated bythe first odometry measurements by a predetermined threshold. In otherwords, filtering criteria may be based on filtering out a crosspoint ifthere is a ranging measurement whose measured distance is smaller thanthe distance between the corresponding measurement point and theinvestigated crosspoint by someone threshold. This logic may generallybe based on the assumption that there are no undershoot measurements,i.e., that the measured range is always greater than or equal to theactual distance (e.g., due to reflections or other effects which mayincrease the path traveled by the measurement signal). After performingthe filtering, only feasible crosspoints may remain, representing asmall and concentrated set of crosspoints from which the algorithm maychoose a cluster head as described above, e.g., using a clusteringalgorithm or an optimization algorithm to determine the cluster headthat is closest to all the possible crosspoints.

The at least two location estimation algorithms may also comprise anoptimization algorithm which includes solving an optimization problem tooptimally fit the locations of the plurality of anchor nodes with thefirst ranging measurements and the first odometry measurements. Suchalgorithm may be seen as a fundamentally different approach to thecrosspoint filtering algorithm because it may try to find the anchornode positions as well as the measurement point positions as a largeoptimization problem such that the estimated positions fit themeasurements in the best possible way. Here, not only the anchor nodepositions may be treated as unknown, but also the measurement pointpositions (i.e., the odometry positions). However, in order to increasethe algorithm convergence time and accuracy, the odometry measurementsmay be treated as known positions. In the optimization algorithm, therespective first positions estimated by the first odometry measurementsmay thus be treated as known positions in the optimization problem. Itwill be understood that a “known” position may here have the meaningthat the algorithm may take into account a certain +/−margin (or errorrange) as uncertainty regarding the measured odometry positions.

Once the locations of the plurality of anchor nodes have been estimatedaccording to the procedure described above, the estimated locations mayfurther be subjected to a validation procedure. The validation proceduremay be performed as part of step S204, for example. To this end, a newset of ranging and odometry measurements may be collected in thelocalization area for validation purposes. The method may thus furthercomprise performing, at a plurality of second measurement points in thelocalization area using the localization tag, second rangingmeasurements with respect to the plurality of anchor nodes using theradio technology to determine respective second distances from themeasurement device to the plurality of anchor nodes and performing, atthe plurality of second measurement points using the at least oneodometry sensor, second odometry measurements to estimate respectivesecond positions of the measurement device in the localization area, andvalidating the estimated locations of the plurality of anchor nodesbased on the second distances determined by the second rangingmeasurements and the second positions estimated by the second odometrymeasurements. The plurality of second measurement points may bedifferent from the plurality of first measurement points and, morespecifically, the second measurement dataset may be collectedindependently from the first measurement dataset. On the other hand, thesecond measurement dataset may be processed in the same manner as thefirst measurement dataset (e.g., transferred from measurement device tothe server, etc.). In particular, the second measurement dataset may besubjected to the same drift compensation as the first measurementdataset, for example.

Validating the estimated locations of the plurality of anchor nodes mayinclude checking whether the locations of the plurality of anchor nodeswhich are estimated based on the second distances and the secondpositions confirm the locations of the plurality of anchor nodes whichare estimated based on the first distances and the first positions. Foran anchor node, the estimated location may be considered to be confirmedwhen the corresponding location that is estimated based on the seconddistances and the second positions equals or is within a predefineddistance threshold to the corresponding location that is estimated basedon the first distances and first positions. Additionally oralternatively, in order to assess whether an estimated location isconfirmed, a number of other metrics may be taking into consideration.For example, validating the estimated locations of the plurality ofanchor nodes may be performed considering at least one of a number ofundershoot measurements corresponding to a number of times one of thesecond distances is smaller than a distance between the associatedsecond position and the estimated location of the corresponding anchornode being validated, a number of line of sight measurementscorresponding to a number of times one of the second distances coincideswith a distance between the associated second position and the estimatedlocation of the corresponding anchor node being validated (this metricmay be calculated for both the original measurements and for thevalidation set), and an angular distribution of the line of sightmeasurements in space (this may indicate whether the validated anchornode has been measured evenly from all main directions; e.g., the spacemay be divided into four regions and it may be calculated from whichregion a given ranging measurement comes from). Based on these metrics,assessing whether an estimated location is confirmed may be performed bychecking whether at least one of these metrics is above or below acorresponding predefined threshold. If an estimated location isconfirmed following any of the above rules, the estimated location maybe said to be positively validated. Otherwise, the estimated locationmay be said to be negatively validated.

If an estimated location of an anchor node is negatively validated, theanchor node may be declared to be unreliable and a correspondingindication may be provided (e.g., via the measurement device). Themeasurement procedure may then be repeated for the negatively validatedanchor nodes to refine their estimated coordinates. Thus, when one ormore of the estimated locations of the plurality of anchor nodes arevalidated negatively, the method may further comprise performing, at aplurality of third measurement points in the localization area using thelocalization tag, third ranging measurements with respect to the one ormore negatively validated anchor nodes using the radio technology todetermine respective third distances from the measurement device to theone or more negatively validated anchor nodes and performing, at theplurality of third measurement points using the at least one odometrysensor, third odometry measurements to estimate respective thirdpositions of the measurement device in the localization area, andrefining the estimated locations of the one or more negatively validatedanchor nodes based on the respective third distances determined by thethird ranging measurements and the respective third positions estimatedby the third odometry measurements. Similar to the second measurementdataset, the thus determined third measurement data set may be processedin the same manner as described above for the first measurement data set(e.g., transferred from the measurement device to the server, etc.). Inparticular, the third measurement data set may be subjected to the samedrift compensation as the first measurement dataset, for example.

As part of the repeated measurement procedure, a user may be givenindications which positions are problematic and which anchor nodesshould thus be re-measured. To this end, the method may further compriseproviding guidance for re-measuring the one or more negatively validatedanchor nodes. Also, feedback on whether or not measurements are line ofsight from a given location may be provided to the user. The method maythus also comprise providing feedback on whether the third rangingmeasurements correspond to line of sight measurements. A user may inthis way be enabled to move the measurement device in such a way thatline of sight is reached.

FIG. 6a schematically illustrates an exemplary partial composition ofthe measurement device described above. The measurement device 602 maycomprise at least one processor 604 and at least one memory 606, whereinthe at least one memory 606 may contain instructions executable by theat least one processor 604 such that the measurement device 602 isoperable to carry out the method steps described above in relation tothe measurement device.

FIG. 6b schematically illustrates an exemplary partial composition ofthe configuration component mentioned above. As said, the configurationcomponent may (but does not necessarily have to) be executed on aserver. The configuration component 612 may comprise at least oneprocessor 614 and at least one memory 616, wherein the at least onememory 616 may contain instructions executable by the at least oneprocessor 614 such that the configuration component 612 is operable tocarry out the method steps described above in relation to theconfiguration component (or the server). It will be understood that, ifthe configuration component 612 is implemented on a server remotely fromthe measurement device, the configuration component 612 may beimplemented on a physical computing unit or a virtualized computingunit, such as a virtual machine, for example. It will further beappreciated that the configuration component 612 may not necessarily beimplemented on a standalone computing unit, but may be implemented ascomponents—realized in software and/or hardware—residing on multipledistributed computing units as well, such as in a cloud computingenvironment, for example.

FIG. 7 illustrates a flowchart of an exemplary calibration procedurewhich is based on the method described above. The left portion of thefigure illustrates steps of the method that are performed in a cloud(e.g., in an offline manner) and the right portion of the figureillustrates the steps of the method that are performed in the fieldusing the measurement device. As an exemplary implementation of themeasurement device, the calibration procedure may be performed using thesmart phone 300, for example. As can be seen in the figure, in aninitial step, measurements are collected in the field by taking randomwalks in the localization area, and software that runs on the phonecontinuously logs ranging measurements as well as odometry measurements.When the measurement collection is completed, the log file is uploadedfrom the phone to the cloud, where any drifts in the odometrymeasurements are compensated by matching odometry positions with knownlandmark positions. Next, two anchor location estimation algorithms areexecuted in parallel, wherein each of the algorithms is robust for adifferent type of error to minimize the error of the procedure. Theoutput of the algorithms is then combined and the resulting coordinatesare taken as the estimated locations of the anchor nodes. In order tovalidate the estimated locations, a new set of field measurements iscollected in the field and uploaded as well as drift compensated in thesame manner as in the first step. The validation is performed to assesswhether the independently collected new data set confirms the previouslyestimated positions of the anchor nodes. If the new measurements confirmthe anchor node coordinates, they are accepted and, if there are anchornodes for which the estimated coordinates and the validationmeasurements are in conflict, the whole procedure is re-run (but onlyfor those selected anchor nodes).

An exemplary result of the calibration procedure is shown in FIG. 8 foran actual deployment. In the figure, filled circles represent theestimated anchor node positions and unfilled circles represent trueanchor node positions. Further, dots indicate the walking path where themeasurements have been collected using the measurement device. As can beseen in figure, anchor nodes that have been visited on the measurementpath “sufficiently well” (e.g., quantifyable in the validation step) allshow a good and accurate estimation of the anchor node positions, whileslight deviations appear in the estimated locations of anchor nodeswhich have not been visited closely on the measurement path.

FIG. 9 illustrates an example of the validation statistics obtained foran actual deployment. The upper diagram in the figure shows the numberof undershoot measurements per anchor node and the lower diagram in thefigure shows the distribution for four measurements directions (i.e.,−180, −90, 0, 90 degrees) corresponding to the angular distribution ofthe line of sight measurements in space. As can be seen in the upperdiagram, for example, the number of undershoot measurements indicatorcoincides well with the true anchor position errors so that it may beconcluded that a higher indicator value provides an indication for ahigher error.

As has become apparent from the above, the present disclosure provides atechnique for calibrating a positioning system which makes use of ameasurement device that integrates both a localization tag and at leastone odometry device in order to provide a more accurate measurementcollection when taking random walk measurements in the localization areafor calibration purposes. Due to the combined device, the trajectory maybe known with improved accuracy. By then executing at least twodifferent algorithms for the purpose of estimating the position of theanchor nodes, wherein one algorithm is robust against one type of errorswhile the other is robust against another type of errors, the algorithmsare more robust in the sense that they are not required to make anyassumptions about hidden models, line of sight or non-line of sightcharacteristics of the measurements being performed. The validationprocedure may then be executed by collecting a new measurement set anddetermining the goodness of the estimated anchor node positions and,when necessary, this procedure may involve reiterating the whole processfor problematic anchor nodes. The validation may give hints on where andhow to collect more measurements to refine inaccurate anchor nodecoordinates. In other words, the validation may iteratively improve thecalibration while providing guidance as to where and how to collect moremeasurements. In sum, the presented technique may provide a convenientand semi-automatic solution for the anchor configuration problem.

It is believed that the advantages of the technique presented hereinwill be fully understood from the foregoing description, and it will beapparent that various changes may be made in the form, constructions andarrangement of the exemplary aspects thereof without departing from thescope of the invention or without sacrificing all of its advantageouseffects. Because the technique presented herein can be varied in manyways, it will be recognized that the invention should be limited only bythe scope of the claims that follow.

1. A method for calibrating a positioning system comprising a pluralityof anchor nodes used to determine tag positions within a localizationarea using radio technology, the method being performed using ameasurement device comprising at least one odometry sensor and alocalization tag configured to communicate with the plurality of anchornodes using the radio technology, the method comprising: performing, ata plurality of first measurement points in the localization area usingthe localization tag, first ranging measurements with respect to theplurality of anchor nodes using the radio technology to determinerespective first distances from the measurement device to the pluralityof anchor nodes and performing, at the plurality of first measurementpoints using the at least one odometry sensor, first odometrymeasurements to estimate respective first positions of the measurementdevice in the localization area; estimating locations of the pluralityof anchor nodes based on the respective first distances determined bythe first ranging measurements and the respective first positionsestimated by the first odometry measurements, estimating the locationsof the plurality of anchor nodes including: executing at least twolocation estimation algorithms having different characteristics withregard to error robustness; and combining the results of the at leasttwo location estimation algorithms; and configuring the positioningsystem with the estimated locations of the plurality of anchor nodes tocalibrate the positioning system.
 2. The method of claim 1, wherein thefirst ranging measurements and the first odometry measurements areperformed periodically when moving the measurement device through thelocalization area.
 3. The method of claim 1, wherein the respectivefirst distances determined by the first ranging measurements and therespective first positions estimated by the first odometry measurementsare stored in a first measurement dataset, wherein, in the firstmeasurement dataset, each position estimated by an odometry measurementis stored in association with corresponding distances to visible anchornodes determined by ranging measurements at the same measurement point.4. The method of claim 1, wherein the respective first distancesdetermined by the first ranging measurements and the respective firstpositions estimated by the first odometry measurements are transferredfrom the measurement device to a server, wherein estimating thelocations of the plurality of anchor nodes is performed by the server.5. The method of claim 4, wherein transferring the respective firstdistances determined by the first ranging measurements and therespective first positions estimated by the first odometry measurementsfrom the measurement device to the server is performed batchwise whileperforming the first ranging measurements and the first odometrymeasurements. 6.-8. (canceled)
 9. The method of claim 1, wherein the atleast two location estimation algorithms comprise a crosspoint basedalgorithm which includes calculating crosspoints of spheres as candidatelocations of anchor nodes, the spheres having centers corresponding tothe first positions estimated by the first odometry measurements andhaving radii corresponding to the associated first distances determinedby the first ranging measurements.
 10. The method of claim 9, wherein alocation of an anchor node is estimated by determining a cluster headthat is closest to the calculated crosspoints.
 11. The method of claim9, wherein the crosspoint based algorithm further includes filtering outcrosspoints for which there are ranging measurements with a distancesmaller than a distance between the respective crosspoint and acorresponding first position estimated by the first odometrymeasurements by a predetermined threshold.
 12. (canceled)
 13. (canceled)14. The method of claim 1, further comprising: performing, at aplurality of second measurement points in the localization area usingthe localization tag, second ranging measurements with respect to theplurality of anchor nodes using the radio technology to determinerespective second distances from the measurement device to the pluralityof anchor nodes and performing, at the plurality of second measurementpoints using the at least one odometry sensor, second odometrymeasurements to estimate respective second positions of the measurementdevice in the localization area; and validating the estimated locationsof the plurality of anchor nodes based on the second distancesdetermined by the second ranging measurements and the second positionsestimated by the second odometry measurements.
 15. The method of claim14, wherein validating the estimated locations of the plurality ofanchor nodes is performed considering at least one of: a number ofundershoot measurements corresponding to a number of times one of thesecond distances is smaller than a distance between the associatedsecond position and the estimated location of the corresponding anchornode being validated; a number of line of sight measurementscorresponding to a number of times one of the second distances coincideswith a distance between the associated second position and the estimatedlocation of the corresponding anchor node being validated; and anangular distribution of the line of sight measurements in space. 16.-18.(canceled)
 19. A measurement device for supporting calibration of apositioning system comprising a plurality of anchor nodes used todetermine tag positions within a localization area using radiotechnology, the measurement device comprising: at least one odometrysensor and a localization tag configured to communicate with theplurality of anchor nodes using the radio technology, the measurementdevice being configured to: perform, at a plurality of first measurementpoints in the localization area using the localization tag, firstranging measurements with respect to the plurality of anchor nodes usingthe radio technology to determine respective first distances from themeasurement device to the plurality of anchor nodes and performing, atthe plurality of first measurement points using the at least oneodometry sensor, first odometry measurements to estimate respectivefirst positions of the measurement device in the localization area;estimate locations of the plurality of anchor nodes based on therespective first distances determined by the first ranging measurementsand the respective first positions estimated by the first odometrymeasurements, estimating the locations of the plurality of anchor nodesincludes: executing at least two location estimation algorithms havingdifferent characteristics with regard to error robustness; and combiningthe results of the at least two location estimation algorithms; andprovide the respective first distances determined by the first rangingmeasurements and the respective first positions estimated by the firstodometry measurements to a configuration component for calibration ofthe positioning system. 20.-27. (canceled)
 28. A configuration componentfor supporting calibration of a positioning system comprising: aplurality of anchor nodes used to determine tag positions within alocalization area using radio technology, the configuration componentbeing configured to: obtain, from a measurement device, respective firstdistances from the measurement device to the plurality of anchor nodesdetermined by first ranging measurements performed by the measurementdevice at a plurality of first measurement points in the localizationarea using a localization tag of the measurement device, and respectivefirst positions of the measurement device in the localization areaestimated by first odometry measurements performed by the measurementdevice at the plurality of first measurement points using at least oneodometry sensor of the measurement device; estimate locations of theplurality of anchor nodes based on the respective first distancesdetermined by the first ranging measurements and the respective firstpositions estimated by the first odometry measurements, estimating thelocations of the plurality of anchor nodes including: executing at leasttwo location estimation algorithms having different characteristics withregard to error robustness; and combining the results of the at leasttwo location estimation algorithms; and configure the positioning systemwith the estimated locations of the plurality of anchor nodes tocalibrate the positioning system.
 29. The configuration component ofclaim 28, wherein the locations of the plurality of anchor nodesincludes compensating drifts in the respective first positions estimatedby the first odometry measurements.
 30. The configuration component ofclaim 28, wherein compensating the drifts in the respective firstpositions estimated by the first odometry measurements includes at leastone of rotating and scaling the respective first positions with respectto at least one known landmark position.
 31. (canceled)
 32. Theconfiguration component of claim 28, wherein the at least two locationestimation algorithms comprise a crosspoint based algorithm whichincludes calculating crosspoints of spheres as candidate locations ofanchor nodes, the spheres having centers corresponding to the firstpositions estimated by the first odometry measurements and having radiicorresponding to the associated first distances determined by the firstranging measurements.
 33. The configuration component of claim 32,wherein a location of an anchor node is estimated by determining acluster head that is closest to the calculated crosspoints.
 34. Theconfiguration component of claim 32, wherein the crosspoint basedalgorithm further includes filtering out crosspoints for which there areranging measurements with a distance smaller than a distance between therespective crosspoint and a corresponding first position estimated bythe first odometry measurements by a predetermined threshold. 35.(canceled)
 36. (canceled)
 37. The configuration component of claim 28,further configured to: obtain, from the measurement device, respectivesecond distances from the measurement device to the plurality of anchornodes determined by second ranging measurements performed by themeasurement device at a plurality of second measurement points in thelocalization area using the localization tag of the measurement devicewith respect to the plurality of anchor nodes, and respective secondpositions of the measurement device in the localization area estimatedby second odometry measurements performed by the measurement device atthe plurality of second measurement points using at least one odometrysensor of the measurement device; and validate the estimated locationsof the plurality of anchor nodes based on the second distancesdetermined by the second ranging measurements and the second positionsestimated by the second odometry measurements.
 38. The configurationcomponent of claim 37, wherein validating the estimated locations of theplurality of anchor nodes is performed considering at least one of: anumber of undershoot measurements corresponding to a number of times oneof the second distances is smaller than a distance between theassociated second position and the estimated location of thecorresponding anchor node being validated; a number of line of sightmeasurements corresponding to a number of times one of the seconddistances coincides with a distance between the associated secondposition and the estimated location of the corresponding anchor nodebeing validated; and an angular distribution of the line of sightmeasurements in space. 39.-41. (canceled)
 42. A system comprising: ameasurement device for supporting calibration of a positioning systemcomprising a plurality of anchor nodes used to determine tag positionswithin a localization area using radio technology, the measurementdevice, the measurement device comprising: at least one odometry sensorand a localization tag configured to communicate with the plurality ofanchor nodes using the radio technology, the measurement device beingconfigured to: perform, at a plurality of first measurement points inthe localization area using the localization tag, first rangingmeasurements with respect to the plurality of anchor nodes using theradio technology to determine respective first distances from themeasurement device to the plurality of anchor nodes and performing, atthe plurality of first measurement points using the at least oneodometry sensor, first odometry measurements to estimate respectivefirst positions of the measurement device in the localization area;estimate locations of the plurality of anchor nodes based on therespective first distances determined by the first ranging measurementsand the respective first positions estimated by the first odometrymeasurements, estimating the locations of the plurality of anchor nodesincludes: executing at least two location estimation algorithms havingdifferent characteristics with regard to error robustness; and combiningthe results of the at least two location estimation algorithms; andprovide the respective first distances determined by the first rangingmeasurements and the respective first positions estimated by the firstodometry measurements to a configuration component for calibration ofthe positioning system; and the configuration component comprising: aplurality of anchor nodes used to determine tag positions within alocalization area using radio technology, the configuration componentbeing configured to: obtain, from a measurement device, respective firstdistances from the measurement device to the plurality of anchor nodesdetermined by first ranging measurements performed by the measurementdevice at a plurality of first measurement points in the localizationarea using a localization tag of the measurement device, and respectivefirst positions of the measurement device in the localization areaestimated by first odometry measurements performed by the measurementdevice at the plurality of first measurement points using at least oneodometry sensor of the measurement device; estimate locations of theplurality of anchor nodes based on the respective first distancesdetermined by the first ranging measurements and the respective firstpositions estimated by the first odometry measurements, estimating thelocations of the plurality of anchor nodes including: executing at leasttwo location estimation algorithms having different characteristics withregard to error robustness; and combining the results of the at leasttwo location estimation algorithms; and configure the positioning systemwith the estimated locations of the plurality of anchor nodes tocalibrate the positioning system.